Search for: predictive-tools
Application of artificial neural networks to prediction of chemical composition of electrodeposited Ni-Mo thin films, Article ECS Transactions ; Volume 50, Issue 52 , Oct , 2012 , Pages 63-71 ; 19385862 (ISSN) ; Rouhaghdam, A. S ; Aliofkhazraie, M ; Shahrabi, T ; Ashrafi, A ; Seddighian, A ; Sharif University of Technology
Present research represents the application of artificial neural networks to predict the chemical composition of electrodeposited Ni-Mo thin films. Artificial neural networks commonly are utilized as a prediction tools so that these networks could approximately find kind of logic relationships between inputs and target; they fitted appropriate coefficient and weighting factors to the inputs which are proportional to their importance. In order to evaluate the model developed, experimental results were compared with the predicted ones. However, more data are required to train more reliable prediction models, presents study revealed an acceptable error less than 1% between predicted values and...
Article Computational Materials Science ; Volume 45, Issue 2 , 2009 , Pages 385-387 ; 09270256 (ISSN) ; Bahrami, A ; Mousavi Anijdan, S. H ; Sharif University of Technology
An age-hardening model has been developed to predict the evolution of the hardness of Al-Mg-Si alloys during non-isothermal ageing before peak age. The concurrent precipitation and dissolution have been considered in the structural model. Then the structural model has been combined with strengthening model to predict the precipitation-hardening behavior of the alloy AA6061. The results indicate that the developed model can be used as a predictive tool to model the mechanical properties evolution of Al-Mg-Si alloys during non-isothermal heat treatment. © 2008 Elsevier B.V. All rights reserved
Article Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics, 24 June 2012 through 27 June 2012 ; June , 2012 , Pages 419-424 ; 21551774 (ISSN) ; 9781457711992 (ISBN) ; Jahed, M ; Sharif University of Technology
Conventional models of cardiovascular system (CV) frequently lack required detail. Once utilized to study the heart function, these models focus primarily on the overall relationship between pressure, flow and volume. This study proposes a localized and regional model of the CV system. It utilizes non-invasive blood flow and pressure seed data and temporal cardiac muscle regional activation to predict the operation of the heart. Proposed localized analysis considers specific regions of the heart, namely base, mid and apex sections of the left ventricle. This modular system is based on a hydraulic electric analogy model, estimating desired parameters, namely resistance (R), compliance (C),...
Article International Journal of Engineering, Transactions A: Basics ; Volume 22, Issue 1 , February , 2009 , Pages 59-68 ; 17281431 (ISSN) ; Rad, M ; Sharif University of Technology
Materials and Energy Research Center 2009
The powering requirement of a land yacht is one of the most important aspects of its design. In this respect the wind tunnel testing is an effective design tool. In fact, changing the parameters of the vehicle and testing the changes in the wind tunnel will give us a better understanding of the most efficient vehicle, and yet it is time consuming, expensive, and has inherent scaling errors. Another set of design tools are Computational Fluid Dynamics and parametric prediction. Computational Fluid Dynamics (CFD) codes are not yet wholly proven in its accuracy. Parametric prediction is the starting point for most engineering studies. It will be used to calculate the land yacht's performance...